Path planning in 1000+ dimensions using a task-space Voronoi bias
Name
Shkolnik-2009-Path planning in 1000+ dimensions using a task-space Voronoi bias.pdf
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262.92 KB
Format
Adobe PDF
Checksum (MD5)
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Author(s)
Shkolnik, Alexander C.
Tedrake, Russell Louis
Date Issued
July 2009
Journal
IEEE International Conference on Robotics and Automation, 2009. ICRA '09
Publisher
Institute of Electrical and Electronics Engineers
Citation
Shkolnik, A., and R. Tedrake. “Path planning in 1000+ dimensions using a task-space Voronoi bias.” Robotics and Automation, 2009. ICRA '09. IEEE International Conference on. 2009. 2061-2067. © 2009 IEEE.
Version
Final published version
Abstract
The reduction of the kinematics and/or dynamics of a high-DOF robotic manipulator to a low-dimension ldquotask spacerdquo has proven to be an invaluable tool for designing feedback controllers. When obstacles or other kinodynamic constraints complicate the feedback design process, motion planning techniques can often still find feasible paths, but these techniques are typically implemented in the high-dimensional configuration (or state) space. Here we argue that providing a Voronoi bias in the task space can dramatically improve the performance of randomized motion planners, while still avoiding non-trivial constraints in the configuration (or state) space. We demonstrate the potential of task-space search by planning collision-free trajectories for a 1500 link arm through obstacles to reach a desired end-effector position.
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Terms of Use
Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1109/ROBOT.2009.5152638
